A new time-dependent wavefunction formulation for the cumulant Green’s functions can produce more accurate simulations.

PNNL researchers received an award from the Materials, Metals & Materials Society (TMS) for a publication on friction riveting.

Scientists are reviewing the current science of the mechanism and structural dynamics of methyl coenzyme-M reductase, an enzyme involved in biological methane conversion.

A team combined experiments and theory to predict the collective properties of electrolyte solutions.

Neural networks techniques enable the efficient capture of electron correlation effects in reduced-dimensionality spaces.

Flexible, high-throughput proteomics approach identifies protein modifications related to pancreatic stress and insulin production.

Under an optical field, nanoparticle attachment in a model system heavily depends on surface roughness.

Directionally biased electrostatic interactions are the key to significantly tuning the reduction potential of iron/sulfur clusters.

Developing a new scheme to more efficiently solve quantum chemistry problems.

Increasing concentrations of ions slows the rate of particle aggregation in boehmite suspensions.

Scientists map how transitions from day to night control gene regulatory networks in cyanobacteria, revealing key orchestrators of metabolic switching.

Scientists uncover how cyanobacteria's circadian cycle controls carbon and energy metabolism, increasing carbon dioxide-to-bioproducts yields.

PNNL is hosting a scientific conference focused directly on understanding and predicting the collection of an organism’s traits.

Chemist Wendy Shaw, a nationally recognized scientific leader, has been chosen to serve as the associate laboratory director for PNNL's Physical and Computational Sciences Directorate.

Researchers have created an algorithm that slashes the calculations necessary to prepare and customize data for quantum computing.

Circadian rhythms of blue-green microbes offer new window into predictive phenomics—how to predict and control the traits of an organism.

Nine national laboratories, including PNNL, bring together over 1,000 scientists for a day to use AI to accelerate scientific discovery.

By combining computational modeling with experimental research, scientists identified a promising composition that reduces the need for a critical material in an alloy that can withstand extreme environments.

This week at AAAS, PNNL scientists discuss phenomics and the factors that influence DNA instructions to bring about the world around us.

PNNL Program Development Office Director Karl Mueller explains how the TEC4 project seeks to make advanced chemical computations accessible to all.